Time-optimal reorientation for rigid satellite with reaction wheels

This article introduces a time-optimal reorientation manoeuvre controller with saturation constraints on both reaction wheels’ torques and angular momentum. The proposed control scheme consists of two parts. The first part is an open-loop time-minimum reorientation trajectory generated by the Legendre pseudospectral method. Actuator dynamics, saturations on control torques and angular momentums of reaction wheels are taken into account in generating the open-loop optimal trajectory. The second part is a closed-loop tracking control law to track the optimised reference trajectory based on attitude error dynamics with reaction wheel dynamics. Numerical simulations show that reaction wheel dynamics play an important role in attitude manoeuvres. The proposed controller performs better for rest-to-rest reorientation manoeuvre than other existing methods.     

基于hp自适应伪谱法的空间机器人路径规划

针对空间机器人运动过程中基座姿态产生较大扰动的问题,基于hp自适应高斯伪谱法提出了一种以基座所受反作用力矩最小为目标函数的空间机器人路径规划方法.首先,综合考虑空间机器人运动过程中存在的关节角度约束、关节角速度约束、控制力矩约束及初始状态和终端状态约束等约束条件,将空间机器人路径规划问题看成满足一系列约束条件和边界条件并实现特定性能指标最优的最优控制问题.其次,结合hp自适应高斯伪谱法（hp-AGPM）与非线性规划技术,求解带有边界约束和路径约束的优化控制问题,得到满足约束且性能指标最优的空间机器人运动轨迹.最后,以平面2自由度空间机械臂为例对所设计方法进行仿真验证,并与其他伪谱法进行对比分析.仿真结果表明：本文算法能在10.6 s的时间内规划出满足各约束条件且容许偏差低于10^-6的最优运动轨迹,并且在计算速度和配点数量上都优于其他伪谱法.     

六自由度机械臂约束预测控制系统的设计

本文提出了一种基于约束预测控制的机械臂实时运动控制方法.该控制方法分为两层,分别设计了约束预测控制器和跟踪控制器.其中,约束预测控制器在考虑系统物理约束的条件下,在线为跟踪控制器生成参考轨迹;跟踪控制器采用最优反馈控制律,使机械臂沿参考轨迹运动.为了简化控制器的设计和在线求解,本文采用输入输出线性化的方式简化机械臂动力学模型.同时,为了克服扰动,在约束预测控制器中引入前馈策略,提出了带前馈一反馈控制结构的预测控制设计.因此,本文设计的控制器可以使机械臂在满足物理约束的条件下快速稳定地跟踪到目标位置.通过在PUMA560机理模型上进行仿真实验,验证了预测控制算法的可行性和有效性.     

Safe-by-design planner–tracker synthesis with a hierarchy of system models

We present a safe-by-design trajectory planning and tracking framework for nonlinear dynamical systems using a hierarchy of system models. The planning layer uses a low-fidelity model to plan a feasible trajectory satisfying the planning constraints, and the tracking layer utilizes the high-fidelity model to design a controller that restricts the error states between the low- and high-fidelity models to a bounded set. The simplicity of the low-fidelity model enables the planning to be performed online (e.g. using Model Predictive Control) and the tracking controller and error bound are derived offline (e.g. using sum-of-squares programming). This error bound is then used by the planner to ensure safety for the combined planner–tracker system To provide freedom in the choice of the low-fidelity model, we allow the tracking error to depend on both the states and inputs of the planner. The goal of this article is to provide a tutorial review of this hierarchical framework and to illustrate it with examples, including a design for vehicle obstacle avoidance.     

Flat trajectory design and tracking with saturation guarantees: a nano-drone application

Abstract

This paper deals with the problem of trajectory planning and tracking of a quadcopter system based on the property of differential flatness. First, B-spline characterisations of the flat output allow for optimal trajectory generation subject to waypoint constraints, thrust and angle constraints while minimising the trajectory length. Second, the proposed tracking control strategy combines feedback linearisation and nested saturation control via flatness. The control strategy provides bounded inputs (thrust, roll and pitch angles) while ensuring the overall stability of the tracking error dynamics. The control parameters are chosen based on the information of the a priori given reference trajectory. Moreover, conditions for the existence of these parameters are presented. The effectiveness of the trajectory planning and the tracking control design is analysed and validated through simulation and experimental results over a real nano-quadcopter platform, the Crazyflie 2.0.     

自由漂浮空间机器人轨迹跟踪的模型预测控制

针对传统控制方法难以解决自由漂浮空间机器人(free-floating space robot, FFSR)轨迹跟踪过程中的各类约束的问题,采用模型预测控制对自由漂浮空间机器人的轨迹跟踪问题进行了研究.在自由漂浮空间机器人拉格朗日动力学模型的基础上,建立了系统伪线性化的扩展状态空间模型;在给定系统的性能指标和各类约束的情况下,基于拉盖尔模型设计相应的离散模型预测控制器,并证明控制器的稳定性,控制器中引入任务空间滑模变量实现了对末端期望位置和期望速度的同时跟踪;以平面二杆自由漂浮空间机器人为例,对无约束末端轨迹跟踪和有约束末端轨迹跟踪两种情况进行对比仿真验证.仿真结果表明,该模型预测控制器不仅可以实现对末端期望轨迹的有效跟踪,还能满足各类约束.     

翻滚目标逼近的虚拟域逆动力学轨迹规划

针对追踪星自主逼近和跟踪翻滚目标特定部位的最优规划问题,提出了一种基于虚拟域逆动力学的多约束最优逼近轨迹规划方法.首先,在翻滚目标本体系下建立追踪星相对于翻滚目标特定部位的相对轨道动力学方程,并建立追踪星本体系相对于翻滚目标期望固连坐标系的相对姿态动力学方程;其次,考虑目标星外形、敏感器视场和执行机构控制能力等约束条件,建立时间/能量最优规划模型;然后,采用序列二次规划(sequential quadratic programming,SQP)方法求解时间/能量最优规划问题;最后,数值仿真验证了该方法在满足多约束条件下,可实现对翻滚目标自主逼近与跟踪的最优轨迹规划,同时与高斯伪谱法进行了对比,验证了本方法在计算效率方面的优势.     

A Mode-Switching Motion Control System for Reactive Interaction and Surface Following Using Industrial Robots

This work proposes a sensor-based control system for fully automated object detection and exploration (surface following) with a redundant industrial robot. The control system utilizes both offline and online trajectory planning for reactive interaction with objects of different shapes and color using RGBD vision and proximity/contact sensors feedback where no prior knowledge of the objects is available. The RGB-D sensor is used to collect raw 3D information of the environment. The data is then processed to segment an object of interest in the scene. In order to completely explore the object, a coverage path planning technique is proposed using a dynamic 3D occupancy grid method to generate a primary (offline) trajectory. However, RGB-D sensors are very sensitive to lighting and provide only limited accuracy on the depth measurements. Therefore, the coverage path planning is then further assisted by a real-time adaptive path planning using a fuzzy self-tuning proportional integral derivative (PID) controller. The latter allows the robot to dynamically update the 3D model by a specially designed instrumented compliant wrist and adapt to the surfaces it approaches or touches. A modeswitching scheme is also proposed to efficiently integrate and smoothly switch between the interaction modes under certain conditions. Experimental results using a CRS-F3 manipulator equipped with a custom-built compliant wrist demonstrate the feasibility and performance of the proposed method.      

卫星编队飞行的鲁棒自适应控制方法

研究了主从式框架下编队飞行的相对控制问题.首先推导了描述主从星相对运动的完整非线性动力学模型, 利用完整模型的无摄动形式提出了最优参考轨迹生成问题,并应用高斯伪谱法将此问题转换成非线性规划问题,使其可以数值求解; 基于Lyapunov 方法设计了闭环系统的鲁棒自适应控制器,在存在未知干扰、未知主星轨道参数与控制以及未知从星质量的情况下, 仅利用相对状态测量即能够保证闭环系统的参考轨迹跟踪误差和参数估计误差全局一致最终有界,并证明了跟踪误差的最终界可以 通过选取合理的控制器参数使其任意小;最后给出了具体的仿真场景验证了本文主要结果的有效性.     

A novel trajectory planning-based adaptive control method for 3-D overhead cranes

A three-dimensional (3-D) overhead crane is a complicated nonlinear underactuated mechanical system, for which high-speed positioning and anti-sway control are the kernel objective. Existing trajectory-based methods for 3-D overhead cranes focus on combining efficient and smooth trajectories with anti-sway tracking controllers without regard for payload motion; moreover, the exact value of plant parameters is required for accurate compensation during the control process. Motivated by these facts, we present a two-step design tracking strategy which consists of a trajectory planning stage and an adaptive tracking control design stage for 3-D overhead cranes. As shown by Lyapunov techniques and Barbalat's Lemma, the proposed controller guarantees asymptotic swing elimination and trolley positioning result in the presence of system uncertainties including unknown parameters and external disturbances. Simulation results also showed the applicability of the proposed method with good robustness against parameter uncertainties and external disturbances.     

Adaptive nonlinear information fusion preview control for autonomous surface vessels subject to measurement noises and unknown input saturations

This study presents an adaptive nonlinear information fusion preview control (NIFPC) method for trajectory tracking of autonomous surface vessels (ASVs) subject to system uncertainty, measurement noise, and unknown input saturations. The NIFPC is developed based on the nonlinear information fusion estimation methodology, in which the system's future reference trajectory information, noise information, performance index requirements, and system dynamic model are all transformed into information equations related to control input, and then the current control action is obtained by fusing these previewed future information via the nonlinear information fusion optimal estimation. In order to avoid the unknown input saturation constraints, a fuzzy asymmetric saturated approximator (FASA) is designed and integrated into the controller, where the fuzzy logic system (FLS) is used to adaptively adjust the key boundary parameters of the approximator. As a result, the negative effects caused by system uncertainty and measurement noise can be effectively suppressed, while the completely unknown input saturation constraints in the system actuator are guaranteed not to be violated. The convergence of the tracking errors of the closed-loop system is guaranteed via Lyapunov stability theory. Numerical simulation results have been provided to demonstrate the satisfactory performance of the proposed control scheme.     

Formation tracking of multi-vehicle systems in unknown environments using a multi-region control scheme

In this paper, a multi-region control scheme is proposed for a formation of nonholonomic vehicles to track a reference trajectory while avoiding collisions and preserving network connectivity in unknown environments. The proposed control scheme defines three regions, safe region, dangerous region and transition region. In different regions, priority is given to different control objectives. In safe region where trajectory tracking holds the priority, the proposed control scheme guarantees bounded tracking of the reference trajectory for each vehicle. In dangerous region where avoidance control is the main objective, a new bounded potential function is designed to characterise constraints of obstacle and inter-vehicle collision avoidance as well as connectivity maintenance. By introducing a series of transition functions, smooth switching between trajectory tracking and avoidance control is achieved in transition region. It has been proved that each vehicle can track its reference trajectory while satisfying the constraints simultaneously with a bounded controller which means that the proposed control scheme satisfies input constraints by properly tuning parameters. Simulation results demonstrate the effectiveness of the proposed method.     

执行器约束下基于数据驱动的参数化前馈控制器设计

针对执行器约束下非重复性点到点运动的轨迹跟踪问题, 提出了一种在执行器约束下基于数据驱动的参数化输入整形滤波器和前馈控制器优化设计算法. 首先对输入整形滤波器以及前馈控制器进行参数化, 然后在目标函数中加入控制信号变化量与控制信号能量的约束, 再采用基于数据驱动的迭代寻优算法得到最优参数, 在该参数下可以实现满足执行器约束条件下的运动控制系统轨迹最优跟踪性能. 并且由于采用了前馈参数化设计方法, 在点到点轨迹发生变化时所提出算法依然能够保持良好的轨迹跟踪性能. 仿真与实验结果表明在执行器约束下所提出算法能够实现最优点到点轨迹跟踪性能, 并且对非重复性点到点轨迹跟踪具有一定的鲁棒性.     

欠驱动三维桥式吊车系统自适应跟踪控制器设计

针对三维桥式吊车系统的欠驱动特性, 设计了一种目标轨迹自适应跟踪控制器. 相比其他常规的三维桥式吊车控制器, 它不需要对吊车模型进行任何近似解耦或线性化处理, 并且考虑了系统所受的摩擦力与空气阻力等干扰. 在负载质量和吊绳绳长等发生变化或存在不确定因素的情况下, 它依然能实现对台车的精确定位与负载摆动的有效抑制. 对于闭环系统的稳定性, 文中通过Lyapunov方法和芭芭拉定理对其进行了理论分析, 随后的实验结果也表明了这种自适应跟踪控制器良好的控制性能和对不确定性因素的适应性.     

基于领导跟随的欠驱动船舶编队跟踪控制

针对具有三自由度欠驱动水面船舶编队控制问题,提出一种基于领导跟随 ( Leader /Follower) 结构的欠驱动水面船舶队形跟踪控制方法。当系统接收到队形控制指令, 每个欠驱动水面船舶按照自己在编队中的角色进行控制,其中Leader 根据任务中的队形指令 完成航迹跟踪控制,而Followers 则依据Leader 的信息和航行中任务中的队形指令完成航迹跟 踪控制。在航迹跟踪控制中,根据期望队形任务指令为每个船舶设计需要跟踪的参考路径和 速度指令; 基于Lyapunov 理论和重定义输出方法设计非线性速度控制器和路径跟踪控制器跟 踪设计路径和速度指令; 稳定性分析证明了队形跟踪误差是一致最终稳定的。仿真结果表明 船舶可以跟踪任意期望曲线队形,从而验证了方法的有效性。     

Motion Control of a Nonholonomic Mobile Manipulator in Task Space

In this paper, the motion control of a mobile manipulator subjected to nonholonomic constraints is investigated. The control objective is to design a computed‐torque controller based on the coupled dynamics of the mobile manipulator. The proposed controller achieves the capability of simultaneous tracking of a reference velocity for the mobile base and a reference trajectory for the end‐effector. The aforementioned reference velocity and trajectory are defined in the task space, such task setting imitates the actual working conditions of a mobile manipulator and thus makes the control problem practical. To solve this tracking problem, a steering velocity is firstly designed based on the first‐order kinematic model of the nonholonomic mobile base via dynamic feedback linearization. The main merit of the proposed steering velocity design is that it directly utilizes the reference velocity set in the task space without requiring the knowledge of a reference orientation. A torque controller is subsequently developed based on a proposed Lyapunov function which explicitly considers the coupled dynamics of the mobile manipulator to ensure the mobile base and end‐effector track the reference velocity and trajectory respectively. This proposed computed‐torque controller is able to realize asymptotic stability of both the base velocity tracking error and the end‐effector motion tracking error. Simulations are conducted to demonstrate the effectiveness of the proposed controller.     

Coordinated control method of space-tethered robot system for tracking optimal trajectory

Space-tethered robot system is a new kind of space robot, which consists of a robot platform, space tether, and operation robot. This paper presents the coordinated control method in order to save thruster fuel of operation robot in the process of tracking the optimal approach trajectory. First, the optimal approach trajectory of an operation robot is designed using the Gauss pseudospectral method, which resulted in continuous optimal control force using the Lagrange interpolation scheme. The optimal control force is optimized and distributed to space tether and thrusters through simulated annealing algorithm in discrete points, which minimized fuel consumption of thrusters. The distributive continuous force is obtained via cubic polynomial fitting of optimal distributive force in 0.1s discrete time point. To tracking the optimal trajectory, Fuzzy Proportional-Derivative controller is designed with the help of optimal distribution force which come from optimization model. Simultaneously, the relative attitude of the operation robot is stabilized using attitude time-delay algorithm through the reaction wheels. Numerical results are presented, demonstrating the validity of saving thruster fuel and well performance in tracking the optimal trajectory.

     

基于动态参考规划的鲁棒Tube模型预测跟踪控制

为实现扰动和约束作用下对系统的最优鲁棒跟踪, 提出一种动态参考规划(DRP)方法, 设计鲁棒Tube模型预测控制器(RTMPC)将系统状态驱动到以最优跟踪点为中心的扰动不变集内. 基于DRP的RTMPC控制方法, 以多步参考为决策变量, 确保在线优化递归可行性的同时, 增加在线优化的自由度; 另外, 通过设定目标函数惩罚标称状态轨迹和参考稳态之间、以及最后一步参考稳态和设定点之间的加权欧式距离, 可实现最优鲁棒跟踪.     

不确定混沌系统的动态神经网络跟踪控制

针对不确定非线性混沌系统，提出了一种基于动态神经网络辨识器的自适应跟踪控制新方法，通过滑模控制技术在线调整动态神经网络辨识器权值，并在获取动态神经网络模型的基础上设计出优化控制器，实现混沌系统的轨道跟踪，对辨识误差和轨道跟踪误差进行分析并证明了它们的有界性，Lorenz混沌系统的仿真实验结果表明了控制策略的有效性。     

A symplectic local pseudospectral method for solving nonlinear state‐delayed optimal control problems with inequality constraints

In this paper, a symplectic local pseudospectral (PS) method for solving nonlinear state‐delayed optimal control problems with inequality constraints is proposed. We first convert the original nonlinear problem into a sequence of linear quadratic optimal control problems using quasi‐linearization techniques. Then, based on local Legendre‐Gauss‐Lobatto PS methods and the dual variational principle, a PS method to solve these converted linear quadratic constrained optimal control problems is developed. The developed method transforms the converted problems into a coupling of a system of linear algebraic equations and a linear complementarity problem. The coefficient matrix involved is sparse and symmetric due to the benefit of the dual variational principle. Converged solutions can be obtained with few iterations because of the local PS method and quasi‐linearization techniques are used. The proposed method can be applied to problems with fixed terminal states or free terminal states, and the boundary conditions and constraints are strictly satisfied. Numerical simulations show that the developed method is highly efficient and accurate.